94 citations · 185 across the 12 of their papers we have counts for
13 papers
Incremental Attractor Neural Network Modelling of the Lifespan Retrieval Curve
Patrícia Pereira, Anders Lansner, Pawel Herman
The human lifespan retrieval curve describes the proportion of recalled memories from each year of life. It exhibits a reminiscence bump - a tendency for aged people to better reca…
Spiking neural networks with Hebbian plasticity for unsupervised representation learning
Naresh Ravichandran, Anders Lansner, Pawel Herman
We introduce a novel spiking neural network model for learning distributed internal representations from data in an unsupervised procedure. We achieved this by transforming the non…
Hebbian fast plasticity and working memory
Anders Lansner, Florian Fiebig, Pawel Herman
Theories and models of working memory (WM) were at least since the mid-1990s dominated by the persistent activity hypothesis. The past decade has seen rising concerns about the sho…
Brain-like combination of feedforward and recurrent network components achieves prototype extraction and robust pattern recognition
Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman
Associative memory has been a prominent candidate for the computation performed by the massively recurrent neocortical networks. Attractor networks implementing associative memory…
Semi-supervised learning with Bayesian Confidence Propagation Neural Network
Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman
Learning internal representations from data using no or few labels is useful for machine learning research, as it allows using massive amounts of unlabeled data. In this work, we u…
StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs
Artur Podobas, Martin Svedin, Steven W. D. Chien +5
The modern deep learning method based on backpropagation has surged in popularity and has been used in multiple domains and application areas. At the same time, there are other --…